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Two-time-scale stochastic functional differential equations with wideband noises and jumps

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  • Liu, Yuanyuan
  • Wen, Zhexin

Abstract

This work examines a class of path-dependent stochastic systems which are hybrid with wideband noise, Poisson jumps and a singularly perturbed Markov chain. The addition of multi-scale Markov chain allows for modeling of discrete events with both fast and slow fluctuation. While this more realistic approach presents analytical challenges due to the non-Markovian formulation resulting from the wideband noise and the singularly perturbed Markov chain. By virtue of the weak convergence method and Itô functional formula, we prove that as ɛ→0, we obtain a Markovian switching jump diffusion. Finally, we offer several examples to illustrate our findings.

Suggested Citation

  • Liu, Yuanyuan & Wen, Zhexin, 2024. "Two-time-scale stochastic functional differential equations with wideband noises and jumps," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    • Handle: RePEc:eee:chsofr:v:182:y:2024:i:c:s0960077924003084
    DOI: 10.1016/j.chaos.2024.114756
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    References listed on IDEAS

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    1. Wu, Zheng & Yin, George & Lei, Dongxia, 2018. "A class of generalized Ginzburg–Landau equations with random switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 324-336.
    2. Weron, R & Bierbrauer, M & Trück, S, 2004. "Modeling electricity prices: jump diffusion and regime switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 39-48.
    3. Emel Savku & Gerhard-Wilhelm Weber, 2018. "A Stochastic Maximum Principle for a Markov Regime-Switching Jump-Diffusion Model with Delay and an Application to Finance," Journal of Optimization Theory and Applications, Springer, vol. 179(2), pages 696-721, November.
    4. Khasminskii, R.Z. & Zhu, C. & Yin, G., 2007. "Stability of regime-switching diffusions," Stochastic Processes and their Applications, Elsevier, vol. 117(8), pages 1037-1051, August.
    5. J. Lars Kirkby & Duy Nguyen, 2020. "Efficient Asian option pricing under regime switching jump diffusions and stochastic volatility models," Annals of Finance, Springer, vol. 16(3), pages 307-351, September.
    6. Yin, George & Wen, Zhexin, 2019. "Stochastic Kolmogorov systems driven by wideband noises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    7. Nguyen, Dang H. & Nguyen, Nhu N. & Yin, George, 2021. "Stochastic functional Kolmogorov equations, I: Persistence," Stochastic Processes and their Applications, Elsevier, vol. 142(C), pages 319-364.
    8. Massimo Costabile & Arturo Leccadito & Ivar Massabó & Emilio Russo, 2014. "A reduced lattice model for option pricing under regime-switching," Review of Quantitative Finance and Accounting, Springer, vol. 42(4), pages 667-690, May.
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